Search results for "Knn classifier"

showing 4 items of 4 documents

Alignment Free Dissimilarities for Nucleosome Classification

2016

Epigenetic mechanisms such as nucleosome positioning, histone modifications and DNA methylation play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have shown a role of DNA sequences in recruitment of epigenetic regulators. For this reason, the use of more suitable similarities or dissimilarity between DNA sequences could help in the context of epigenetic studies. In particular, alignment-free dissimilarities have already been successfully applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles…

0301 basic medicineNearest neighbour classifiersKnn classifierSettore INF/01 - Informatica030102 biochemistry & molecular biologybiologyComputer scienceSpeech recognitionEpigeneticContext (language use)Computational biologyL-tuples03 medical and health sciences030104 developmental biologyHistoneSimilarity (network science)DNA methylationbiology.proteinNucleosomeEpigeneticsAlignment free DNA sequence dissimilaritiesk-mersNucleosome classificationEpigenomics
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2014

Codebook is an effective image representation method. By clustering in local image descriptors, a codebook is shown to be a distinctive image feature and widely applied in object classification. In almost all existing works on codebooks, the building of the visual vocabulary follows a basic routine, that is, extracting local image descriptors and clustering with a user-designated number of clusters. The problem with this routine lies in that building a codebook for each single dataset is not efficient. In order to deal with this problem, we investigate the influence of vocabulary sizes on classification performance and vocabulary universality with the kNN classifier. Experimental results in…

Vocabularybusiness.industryApplied Mathematicsmedia_common.quotation_subjectInformationSystems_INFORMATIONSTORAGEANDRETRIEVALVisual descriptorsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCodebookPattern recognitionKnn classifierUniversality (dynamical systems)ComputingMethodologies_PATTERNRECOGNITIONImage representationArtificial intelligenceCluster analysisbusinessAnalysisMathematicsmedia_commonAbstract and Applied Analysis
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Feature selection for KNN classifier to improve accurate detection of subthalamic nucleus during deep brain stimulation surgery in Parkinson’s patien…

2017

The tremor and dystonia associated with Parkinson’s disease can be treated with deep brain stimulation (DBS) implanted into the subthalamic nucleus (STN). The accurate STN detection is a complex neurosurgeon task during a DBS surgery since a proper fixing of stimulating electrodes will impact on the patient’s future life. The brain electrical signals obtained with Micro Electrodes Register (MER) are acquired at different depths of the brain during DBS surgery to detect STN. In our previous work, we found good accuracy performance to improve the localization of STN using K-Nearest Neighbours (KNN) supervised learning algorithm. However, for real-time classification, it is essential to reduce…

Deep brain stimulationComputer sciencemedicine.medical_treatmentFeature selection02 engineering and technology03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineDystoniabusiness.industryPattern recognitionmedicine.diseasenervous system diseasesKnn classifierSubthalamic nucleussurgical procedures operativeFeature Dimensionnervous system020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)Neuroscience030217 neurology & neurosurgeryDeep brain stimulation surgery
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Alignment free Dissimilarities for sequence classification

2015

One way to represent a DNA sequence is to break it down into substrings of length L, called L-tuples, and count the occurence of each L-tuple in the sequence. This representation defines a mapping of a sequence into a numerical space by a numerical feature vector of fixed length, that allows to measure sequence similarity in an alignment free way simply using disssimilarity functions between vectors. This work presents a benchmark study of 4 alignment free disssimilarity functions between sequences, computed on their L-tuples representation, for the purpose of sequence classification. In our experiments, we have tested the classes of geometric-based, correlation-based and information-based …

Settore INF/01 - Informaticak-mers L-tuples DNA sequence similarity DNA sequence classification Knn classifier
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